Merge branch 'master' of https://lab.compute.dtu.dk/s183917/ml_data

docs/report/tex/report3.tex

@@ -6,6 +6,7 @@
 
 \usepackage{texfiles/SpeedyGonzales}
 \usepackage{texfiles/MediocreMike}
+\usepackage{booktabs}
 
 % \geometry{top=1cm}
 
@@ -126,11 +127,30 @@ In this part of the report, the data has to be binarized in order to use the Apr
 \subsection{Apriori Algorithm for Frequent Itemsets and Association Rules}
 \textit{Find the frequent itemsets and the association rules with high confidence based on the results of the Apriori algorithm.} \\
 
-Hej Per Parametre
+
+
+Hej Per-parametre
 \[
 \texttt{minsup} = 	0.11\qquad \texttt{minconf} = 0.6
 \]
 
+	\begin{table}[H]
+		\centering
+		\begin{tabular}{l l l r r}
+			\toprule
+			Association Rule &  &  & Support & Confidence \\ \midrule
+			\{energy\_low\} & $\rightarrow$ & \{loudness\_low\}   & 0.226   & 0.674  \\   
+			\{loudness\_low\} & $\rightarrow$ & \{energy\_low\}   & 0.226    & 0.676  \\  
+			\{energy\_high\} & $\rightarrow$ & \{loudness\_high\}   & 0.210    & 0.634 \\  
+			\{loudness\_high\} & $\rightarrow$ & \{energy\_high\}   & 0.210    & 0.631 \\  \\ 
+			\{acousticness\_high, energy\_low\} & $\rightarrow$ & \{loudness\_low\}   &  0.142    & 0.740\\   
+			\{loudness\_low, acousticness\_high\} & $\rightarrow$ & \{energy\_low\}   &  0.142    & 0.842  \\
+			\{loudness\_low, energy\_low\} & $\rightarrow$ & \{acousticness\_high\}   &  0.142    & 0.631  \\ \\
+			\{valence\_low, energy\_low\} & $\rightarrow$ & \{loudness\_low\}   &  0.112    & 0.708  \\
+			\{loudness\_low, valence\_low\} & $\rightarrow$ & \{energy\_low\}   &  0.112    & 0.833  \\ \bottomrule
+		\end{tabular}
+	\end{table}
+
 %{energy_q1} -> {loudness_q1}  (supp: 0.226, conf: 0.674)
 %{loudness_q1} -> {energy_q1}  (supp: 0.226, conf: 0.676)
 %{energy_q3} -> {loudness_q3}  (supp: 0.210, conf: 0.634)